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RigoBERTa: A State-of-the-Art Language Model For Spanish

2022-04-27 · Alejandro Vaca Serrano, Guillem Garcia Subies, Helena Montoro Zamorano, Nuria Aldama Garcia, Doaa Samy, David Betancur Sanchez, Antonio Moreno Sandoval, Marta Guerrero Nieto, Alvaro Barbero Jimenez

This paper presents RigoBERTa, a State-of-the-Art Language Model for Spanish. RigoBERTa is trained over a well-curated corpus formed up from different subcorpora with key features. It follows the DeBERTa architecture, which has several advantages over other architectures of similar size as BERT or RoBERTa. RigoBERTa performance is assessed over 13 NLU tasks in comparison with other available Spanish language models, namely, MarIA, BERTIN and BETO. RigoBERTa outperformed the three models in 10 out of the 13 tasks, achieving new "State-of-the-Art" results.

📄 PDF Abstract BibTeX arXiv:2205.10233

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Language ModelingLanguage Modelling

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Multi-Head Attention 설명 없음
Attention 설명 없음
Linear Layer A Linear Layer is a projection $\mathbf{XW + b}$.
Weight Decay 설명 없음
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Dense Connections Dense Connections, or Fully Connected Connections, are a type of layer in a deep neural network that use a linear operation where every input is connected to every output…
Linear Warmup With Linear Decay Linear Warmup With Linear Decay is a learning rate schedule in which we increase the learning rate linearly for $n$ updates and then linearly decay afterwards.

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